Blog Topic
Top Developer Articles
Architecture and implementation articles for engineering and product teams shipping age verification.
How to use this topic page
Start with one article tied to a decision you need to make this week.
Write down one action, one owner, and one review date before moving to the next article.
Need broader context? Visit the full blog hub for all topics.
All articles
Why We Built Age Verify
Why we built privacy-first in-browser biometric age verification with no ID required.
How biometric age verification works
A plain-English explainer on age estimation, liveness checks, and KYC tradeoffs.
Designing biometric challenge policies
A framework for balancing security thresholds and user completion rates in production flows.
Biometric age verification use cases
Where privacy-first in-browser biometric verification works best across product categories.
Biometric Age Estimation vs. KYC: When to Use Each for Age Verification
When to use biometric age estimation vs full KYC for age-gated product flows.
Developer rollout guide
- This page is for teams implementing age verification in a production stack, not for high-level vendor browsing.
- Start with one journey and define your backend enforcement point before any UI tuning work begins.
- Use idempotency and retry rules early so duplicate requests cannot create conflicting decisions.
- Treat webhook handling as a core reliability path with ownership, alerting, and replay-safe processing.
- Create a short implementation checklist for every release: session lifecycle, retry behavior, escalation handling, and support scripts.
- Use weekly telemetry reviews to compare completion, retry causes, and no-pass outcomes across device segments.
- When quality drops, update prompts and thresholds with controlled experiments instead of broad one-shot changes.
- Document each policy change with owner, reason, expected impact, and review date so teams can audit decisions later.
A common failure pattern is shipping a strong demo path but weak operational handling when retries, delayed events, or partial failures appear in real traffic. Teams avoid this by writing one implementation guide that covers happy path and failure path together.
Another frequent issue is fragmented ownership. Product may own UX, engineering may own backend state, and support may own user messaging, but no single owner checks for policy consistency across all three layers. Set one review checkpoint where all owners verify behavior against the same release goals.
Use a small release checklist before every rollout: session creation behavior, token expiry behavior, finalize retry behavior, escalation route behavior, and support response behavior. This checklist keeps implementation quality stable even when requirements change quickly.
Example planning prompt: what could fail this week, how will we detect it, and who owns recovery if users are blocked unexpectedly?